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Commonalities in the classical, collapsibility and counterfactual concepts of confounding

2004· review· en· W2044678740 on OpenAlexaff
Stephen C. Newman

Bibliographic record

VenueJournal of Clinical Epidemiology · 2004
Typereview
Languageen
FieldMathematics
TopicAdvanced Causal Inference Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCounterfactual thinkingConfoundingCounterfactual conditionalEconometricsKey (lock)AbstractionComputer scienceCovariateObservational studyMedicineRisk analysis (engineering)StatisticsMathematicsPsychologyEpistemologySocial psychologyComputer security

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptualhigh
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptualhigh
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.050
metaresearch head score (Gemma)0.180
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.309
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0500.180
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0100.001
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.785
GPT teacher head0.682
Teacher spread0.104 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designTheoretical or conceptual
DomainMethods
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2004
Admission routes1
Has abstractno

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